This article is part of our Nerd Alert series.
When you talk about epic miniseries events, it's impossible to ignore titles like Alex Haley's Roots or that star-studded Western, Lonesome Dove.
But in terms of heart-pounding excitement and mind-bending analysis, it's almost universally acknowledged that the Nerd Alert's True-Shooting Percentage (TS%) series (of which this is the second installment) is No. 1 in the hearts of the people.
Attentive readers will remember that, in the first installment of our series, we looked at the relationship between TS% and the three fantasy categories it most directly reflects -- i.e. field-goal percentage (FG%), free-throw percentage (FT%), and three-pointers made.
While the data showed that, in fact, TS% did a decent job of projecting fantasy value in those three categories, when we applied the best-fit equation to actual players, it seemed as though it (i.e. the equation) was missing on certain types of players. In particular, we saw it undershoot players with exceptional free-throwing shooting and with three-point skills, too. Contrarily, we saw it overshoot basically the opposite sort of player -- i.e. poor free-throw shooters with hardly any kind of outside game.
I ended that first dispatch with the following note:
True-Shooting Percentage might work as a nice shorthand way of targeting players with good production in the three cats, but it's likely that an even better way is to target players who sport a considerable difference in their TS% and FG% -- or what we might call "secondary" shooting skills.
In this second edition of the series that everyone's
When you talk about epic miniseries events, it's impossible to ignore titles like Alex Haley's Roots or that star-studded Western, Lonesome Dove.
But in terms of heart-pounding excitement and mind-bending analysis, it's almost universally acknowledged that the Nerd Alert's True-Shooting Percentage (TS%) series (of which this is the second installment) is No. 1 in the hearts of the people.
Attentive readers will remember that, in the first installment of our series, we looked at the relationship between TS% and the three fantasy categories it most directly reflects -- i.e. field-goal percentage (FG%), free-throw percentage (FT%), and three-pointers made.
While the data showed that, in fact, TS% did a decent job of projecting fantasy value in those three categories, when we applied the best-fit equation to actual players, it seemed as though it (i.e. the equation) was missing on certain types of players. In particular, we saw it undershoot players with exceptional free-throwing shooting and with three-point skills, too. Contrarily, we saw it overshoot basically the opposite sort of player -- i.e. poor free-throw shooters with hardly any kind of outside game.
I ended that first dispatch with the following note:
True-Shooting Percentage might work as a nice shorthand way of targeting players with good production in the three cats, but it's likely that an even better way is to target players who sport a considerable difference in their TS% and FG% -- or what we might call "secondary" shooting skills.
In this second edition of the series that everyone's talking about, we'll look more deeply at "secondary" shooting -- that is, again, the difference between a player's TS% and his FG%. Player with high secondary shooting sport efficient and/or prolific free-throw and three-point numbers. Players with low secondary scoring numbers are generally poor in these areas.
Among qualified players (of which there are 115), here are the top-10 players by secondary shooting percentage (Sec%) in the league:
And here are the bottom-10 players by secondary shooting percentage (Sec%) in the league:
Looking at those qualified players, here's the relationship we looked at last week, between TS% and the three cats:
As noted, the equation there, while decent, appeared to undershoot one kind of player and overshoot another kind. Furthermore, the correlation coefficient of .54 -- while not terrible -- isn't necessarily ideal, either.
So, what happens when we look at secondary shooting instead? Glad you asked, reader.
Voila:
So, that's pretty good. Not only do we see a similarly shaped slope as in the TS% graph, but we also see a pretty nice upgrade in correlation -- from 54% to 65%.
But how does our equation look? In the first instance -- with TS% -- we saw that it broke down in the extremes. What does Sec% do for us? Well, let's look.
The equation we'll use is the one you see in the image above: (12.089 * Sec%) - 1.3619.
As before, we'll look both at the players our equation undershot -- like these:
And overshot -- like these:
The immediately obvious positive here is that we appear to have made up for some of the problems from before. On the latter of our lists, we see some familiar names from the "overshot" list -- Dwight Howard, Blake Griffin, Andrew Bogut -- but we also see some players -- Gerald Wallace, Andre Iguodala, Kyle Lowry -- with considerably larger Sec%s and totally different skill sets.
The implication of this is a positive one. Instead of seeing blatant misses with a very specific "type" of player, we're seeing some of those misses, but also combined with players whose presence on this list is more probably the result of random variance, as opposed to a problem with the equation, specifically.
So, our conclusion for the day is that -- perhaps somehwat suprisingly -- Sec% is actually more effective that TS% at identifying the best players in the fantasy categories of FG%, FT%, and threes. That in itself is something pretty helpful for fantasy owners. While more information is assuredly always beneficial, Sec% at least gets us about two-thirds of the way towards having a completely accurate shorthand for three categories that are ubiquitous in fantasy play.
